achim.rabus · PyLaia · Published November 8, 2022
Russian generic handwriting 1
Text Recognition
Description
This first version of a generic model for handwritten Russian (predominantly late 19th/early 20th century) was trained as part of the MultiHTR project (Freiburg/Germany, www.multihtr.uni-freiburg.de). It incorporates models trained by the Estonian State Archive and the Hamburg-based INEL project. Portions of the GT data have kindly been provided by the Prozhito project (Saint Petersburg) and the Ukraine RD of JewishGen, USA.
In some of the GT transcriptions, pre-1918 letters have been represented faithfully, while in other GT transcriptions, they have been replaced with their modern equivalents.
Creator: Achim Rabus
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Low error rate6.4% CER
Character Error Rate (CER) measures the percentage of characters incorrectly recognised. Lower is better. This model scored 6.4% on its validation set. As a rule of thumb, a CER below 10% is considered good for most handwritten material. This is a larger model trained on diverse material, which generally makes it more robust across different handwriting styles. That said, larger training sets also make it harder to push the CER down further.
Measured on the model's own validation data. Results on your documents may differ depending on handwriting style, document condition, language, and how closely your material resembles the training data.
Words259,691
Lines57,523
Training Pages2,389
Model ID45988